A Primer Of Ecological Statistics

by Nicholas J. Gotelli, Aaron M. Ellison

A Primer of Ecological Statistics explains fundamental material in probability theory and experimental design for ecologists and environmental scientists. The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject. The book is divided into three parts. Part I discusses the fundamentals of probability and statistical thinking. It introduces the logic and language of probability (Chapter 1), explains common statistical distributions used in ecology (Chapter 2) and important measures of central tendency and spread (Chapter 3), explains P-values, hypothesis testing, and statistical errors (Chapter 4), and introduces frequentist, Bayesian, and Monte Carlo methods of analysis (Chapter 5). Part II discusses how to successfully design and execute field experiments and sampling studies. Topics include design strategies (Chapter 6), a "bestiary" of experimental designs (Chapter 7), and transformations and data management (Chapter 8). Part III discusses specific analyses, and covers the material that is the main core of most statistics texts. Topics include regression (Chapter 9), analysis of variance (Chapter 10), categorical data analysis (Chapter 11), and multivariate analysis (Chapter 12). The book includes a comprehensive glossary, a mathematical appendix on matrix algebra, and extensively annotated tables and figures. Footnotes introduce advanced and ancillary some are purely historical, others cover mathematical/statistical proofs or details, and still others address current topics in the ecological literature.

Genres: Ecology, Science

492 pages, Paperback

First published May 1, 2004

Reviews

[Becky · Rating 5 out of 5]

A great compilation of statistical tests to use in ecology. The reason these tests are good for ecology is because they allow you to express the results of experiments and observations with many factors and many possible outcomes. In ecology the data is varied over time, size scale, temperature, and other continuous variables that are hard to divide up, and this book helps you do that.

I would not call this book a "Primer." It was the main textbook for a statistics course I took in college, and i had previously taken AP statistics in high school. Students with no previous experience in statistics had a much harder time with it. The writing is mostly solid, but there were times when the concepts were not explained in a way that was clear to me. They could have done a slightly better job considering the state of mind of someone who is unfamiliar with statistics.

[Chris · Rating 4 out of 5]

The fact that this book listed among my goodreads speaks volumes about my nerdiness. But the fact is that the Primer is wonderfully readable and has been very useful to me in my research. I love the easy-going writing style, clear explanations, occasional dry humor, and the interesting history footnotes throughout. If you want to refresh your knowledge on basic statistics, especially as it involves ecological research, then I highly recommend this book.

[Cristina · Rating 1 out of 5]

There are much more clear and precise statistical books out there. Read those instead of trying to slog through this one.

[James Harrison · Rating 4 out of 5]

Really helped me understand statistic application to ecology. The examples and descriptions were really great.

[Marcos Egea gutiérrez-cortines · Rating 5 out of 5]

Great book

[Jenny · Rating 4 out of 5]

4.5 stars Very readable with clear explanations behind statistical methods.

[Catherine Normand]

Not the worst statistics book I've ever read.

[Sergio Uribe · Rating 5 out of 5]

Utilicé este libro como referencia para el curso de bioestadística avanzada del doctorado. Absolutamente recomendable porque enfoca el análisis desde el punto de vista del diseño de estudios y la hipótesis, lo que hace mucho más comprensible y facilita la digestión estadística.